A machine-learning-based framework for contractor selection and order allocation in public construction projects considering sustainability, risk, and safety-Reference-Cited by-同舟云学术

A machine-learning-based framework for contractor selection and order allocation in public construction projects considering sustainability, risk, and safety

Published:2024-03-07 Issue:1 Volume:338 Page:225-267
ISSN:0254-5330
Container-title:Annals of Operations Research
language:en
Short-container-title:Ann Oper Res

Author:

Jain Shrey,Jauhar Sunil Kumar^ORCID,Piyush

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s10479-024-05898-6.pdf

Reference54 articles.

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3. Afshar, M. R., Shahhosseini, V., & Sebt, M. H. (2022). Optimal sub-contractor selection and allocation in a multiple construction project: Project portfolio planning in practice. Journal of the Operational Research Society, 73(2), 351–364. https://doi.org/10.1080/01605682.2020.1835450

4. Afzal, A., Aabid, A., Khan, A., Khan, S. A., Rajak, U., Verma, T. N., & Kumar, R. (2020). Response surface analysis, clustering, and random forest regression of pressure in suddenly expanded high-speed aerodynamic flows. Aerospace Science and Technology, 107, 106318. https://doi.org/10.1016/j.ast.2020.106318

5. Alaloul, W. S., Liew, M. S., Wan Zawawi, N. A., Mohammed, B. S., & Adamu, M. (2018). An artificial neural networks (ANN) model for evaluating construction project performance based on coordination factors. Cogent Engineering, 5(1), 1507657.

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